Articles | Volume 25, issue 9
https://doi.org/10.5194/hess-25-5105-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-5105-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Sep 2021
Research article |
| 22 Sep 2021
| 22 Sep 2021
A comparison of tools and techniques for stabilising unmanned aerial system (UAS) imagery for surface flow observations
Robert Ljubičić
CORRESPONDING AUTHOR
Department of Hydraulic and Environmental Engineering, Faculty of
Civil Engineering, University of Belgrade, Belgrade 11120, Serbia
Dariia Strelnikova
School of Geoinformation, Carinthia University of Applied Sciences, Villach 9524, Austria
Matthew T. Perks
School of Geography, Politics and Sociology, Newcastle University,
Newcastle upon Tyne NE1 7RU, United Kingdom
Anette Eltner
Institute of Photogrammetry and Remote Sensing, Technische
Universität Dresden, 01069 Dresden, Germany
Salvador Peña-Haro
Photrack AG, Ankerstrasse 16a, 8004 Zurich, Switzerland
Alonso Pizarro
Escuela de Ingeniería en Obras Civiles, Universidad Diego
Portales, 8370109 Santiago, Chile
Silvano Fortunato Dal Sasso
Department of European and Mediterranean Cultures: Architecture,
Environment and Cultural Heritage (DICEM), University of Basilicata, 75100
Matera, Italy
Ulf Scherling
School of Geoinformation, Carinthia University of Applied Sciences, Villach 9524, Austria
Pietro Vuono
Department of Civil, Architectural and Environmental Engineering,
University of Naples Federico II, 80125 Naples, Italy
Salvatore Manfreda
Department of Civil, Architectural and Environmental Engineering,
University of Naples Federico II, 80125 Naples, Italy
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Alonso Pizarro, Silvano F. Dal Sasso, Matthew T. Perks, and Salvatore Manfreda
Hydrol. Earth Syst. Sci., 24, 5173–5185, https://doi.org/10.5194/hess-24-5173-2020, https://doi.org/10.5194/hess-24-5173-2020, 2020
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T. S. Akiyama, J. Marcato Junior, W. N. Gonçalves, P. O. Bressan, A. Eltner, F. Binder, and T. Singer
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 1189–1193, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1189-2020, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1189-2020, 2020
Matthew T. Perks, Silvano Fortunato Dal Sasso, Alexandre Hauet, Elizabeth Jamieson, Jérôme Le Coz, Sophie Pearce, Salvador Peña-Haro, Alonso Pizarro, Dariia Strelnikova, Flavia Tauro, James Bomhof, Salvatore Grimaldi, Alain Goulet, Borbála Hortobágyi, Magali Jodeau, Sabine Käfer, Robert Ljubičić, Ian Maddock, Peter Mayr, Gernot Paulus, Lionel Pénard, Leigh Sinclair, and Salvatore Manfreda
Earth Syst. Sci. Data, 12, 1545–1559, https://doi.org/10.5194/essd-12-1545-2020, https://doi.org/10.5194/essd-12-1545-2020, 2020
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We present datasets acquired from seven countries across Europe and North America consisting of image sequences. These have been subjected to a range of pre-processing methods in preparation for image velocimetry analysis. These datasets and accompanying reference data are a resource that may be used for conducting benchmarking experiments, assessing algorithm performances, and focusing future software development.
Anette Eltner, Hannes Sardemann, and Jens Grundmann
Hydrol. Earth Syst. Sci., 24, 1429–1445, https://doi.org/10.5194/hess-24-1429-2020, https://doi.org/10.5194/hess-24-1429-2020, 2020
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M. Kröhnert and A. Eltner
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 543–550, https://doi.org/10.5194/isprs-archives-XLII-2-543-2018, https://doi.org/10.5194/isprs-archives-XLII-2-543-2018, 2018
H. Sardemann, A. Eltner, and H.-G. Maas
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 1023–1027, https://doi.org/10.5194/isprs-archives-XLII-2-1023-2018, https://doi.org/10.5194/isprs-archives-XLII-2-1023-2018, 2018
D. Lin, A. Eltner, H. Sardemann, and H.-G. Maas
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2, 201–208, https://doi.org/10.5194/isprs-annals-IV-2-201-2018, https://doi.org/10.5194/isprs-annals-IV-2-201-2018, 2018
Guiomar Ruiz-Pérez, Julian Koch, Salvatore Manfreda, Kelly Caylor, and Félix Francés
Hydrol. Earth Syst. Sci., 21, 6235–6251, https://doi.org/10.5194/hess-21-6235-2017, https://doi.org/10.5194/hess-21-6235-2017, 2017
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Plants are shaping the landscape and controlling the hydrological cycle, particularly in arid and semi-arid ecosystems. Remote sensing data appears as an appealing source of information for vegetation monitoring, in particular in areas with a limited amount of available field data. Here, we present an example of how remote sensing data can be exploited in a data-scarce basin. We propose a mathematical methodology that can be used as a springboard for future applications.
Matthew T. Perks, Andrew J. Russell, and Andrew R. G. Large
Hydrol. Earth Syst. Sci., 20, 4005–4015, https://doi.org/10.5194/hess-20-4005-2016, https://doi.org/10.5194/hess-20-4005-2016, 2016
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Unmanned aerial vehicles (UAVs) have the potential to capture information about the earth’s surface in dangerous and previously inaccessible locations. Here we present a method whereby image acquisition and subsequent analysis have enabled the highly dynamic and oft-immeasurable hydraulic phenomenon present during high-energy flash floods to be quantified at previously unattainable spatial and temporal resolutions.
Matthew Thomas Perks and Jeff Warburton
Earth Surf. Dynam., 4, 705–719, https://doi.org/10.5194/esurf-4-705-2016, https://doi.org/10.5194/esurf-4-705-2016, 2016
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We appraise the success of a novel mitigation approach and subsequent adaptive management, designed to reduce the transfer of fine sediment in a small upland catchment in the UK. Analysis of the river response demonstrates that the fluvial sediment system has become more restrictive with reduced fine sediment transfer. The study demonstrates that channel reconfiguration can be effective in mitigating fine sediment flux in upland streams but the full value of this may take many years to achieve.
A. Eltner, D. Schneider, and H.-G. Maas
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B5, 813–819, https://doi.org/10.5194/isprs-archives-XLI-B5-813-2016, https://doi.org/10.5194/isprs-archives-XLI-B5-813-2016, 2016
Anette Eltner, Andreas Kaiser, Carlos Castillo, Gilles Rock, Fabian Neugirg, and Antonio Abellán
Earth Surf. Dynam., 4, 359–389, https://doi.org/10.5194/esurf-4-359-2016, https://doi.org/10.5194/esurf-4-359-2016, 2016
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Three-dimensional reconstruction of earth surfaces from overlapping images is a promising tool for geoscientists. The method is very flexible, cost-efficient and easy to use, leading to a high variability in applications at different scales. Performance evaluation reveals that good accuracies are achievable but depend on the requirements of the individual case study. Future applications and developments (i.e. big data) will consolidate this essential tool for digital surface mapping.
S. Manfreda, L. Brocca, T. Moramarco, F. Melone, and J. Sheffield
Hydrol. Earth Syst. Sci., 18, 1199–1212, https://doi.org/10.5194/hess-18-1199-2014, https://doi.org/10.5194/hess-18-1199-2014, 2014
S. F. Dal Sasso, A. Sole, S. Pascale, F. Sdao, A. Bateman Pinzòn, and V. Medina
Nat. Hazards Earth Syst. Sci., 14, 557–567, https://doi.org/10.5194/nhess-14-557-2014, https://doi.org/10.5194/nhess-14-557-2014, 2014
Related subject area
Subject: Engineering Hydrology | Techniques and Approaches: Instruments and observation techniques
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Seyed Mohammad Hassan Erfani, Corinne Smith, Zhenyao Wu, Elyas Asadi Shamsabadi, Farboud Khatami, Austin R. J. Downey, Jasim Imran, and Erfan Goharian
Hydrol. Earth Syst. Sci., 27, 4135–4149, https://doi.org/10.5194/hess-27-4135-2023, https://doi.org/10.5194/hess-27-4135-2023, 2023
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Predicting flood magnitude and location helps decision-makers to better prepare for flood events. To increase the speed and availability of data during flooding, this study presents a vision-based framework for measuring water levels and detecting floods. The deep learning models use time-lapse images captured by surveillance cameras to detect water extent using semantic segmentation and to transform them into water level values with the help of lidar data.
Ravi Kumar Meena, Sumit Sen, Aliva Nanda, Bhargabnanda Dass, and Anurag Mishra
Hydrol. Earth Syst. Sci., 26, 4379–4390, https://doi.org/10.5194/hess-26-4379-2022, https://doi.org/10.5194/hess-26-4379-2022, 2022
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We developed a mobile operated programmable rainfall simulator (RS) to simulate the near-natural moving storm rainfall condition and to study its impact on runoff, soil erosion, and nutrient transport. The designed RS can be used for variable velocity and slope conditions along with the three different soil types at a time. Moreover, the soil flume of the RS is associated with the surface, subsurface, and base flow components.
Alonso Pizarro, Silvano F. Dal Sasso, Matthew T. Perks, and Salvatore Manfreda
Hydrol. Earth Syst. Sci., 24, 5173–5185, https://doi.org/10.5194/hess-24-5173-2020, https://doi.org/10.5194/hess-24-5173-2020, 2020
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An innovative approach is presented to optimise image-velocimetry performances for surface flow velocity estimates (and thus remotely sensed river discharges). Synthetic images were generated under different tracer characteristics using a numerical approach. Based on the results, the Seeding Distribution Index was introduced as a descriptor of the optimal portion of the video to analyse. A field case study was considered as a proof of concept of the proposed framework showing error reductions.
Andrea Libertino, Daniele Ganora, and Pierluigi Claps
Hydrol. Earth Syst. Sci., 22, 2705–2715, https://doi.org/10.5194/hess-22-2705-2018, https://doi.org/10.5194/hess-22-2705-2018, 2018
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A new comprehensive dataset of annual maximum rainfall depths recorded in 1 to 24 consecutive hours in Italy is presented. More than 4500 stations are considered, spanning the period between 1916 and 2014. For the first time, a national dataset of annual maxima allows for an updated characterization of rainstorms in Italy, getting rid of the regional borders. The spatio-temporal analyses of the highest rainstorms represent a robust starting point for the assessment of the extreme rainfall risk.
G. Blöschl, T. Nester, J. Komma, J. Parajka, and R. A. P. Perdigão
Hydrol. Earth Syst. Sci., 17, 5197–5212, https://doi.org/10.5194/hess-17-5197-2013, https://doi.org/10.5194/hess-17-5197-2013, 2013
A. Chebbi, Z. K. Bargaoui, and M. da Conceição Cunha
Hydrol. Earth Syst. Sci., 17, 4259–4268, https://doi.org/10.5194/hess-17-4259-2013, https://doi.org/10.5194/hess-17-4259-2013, 2013
V. Merwade and B. L. Ruddell
Hydrol. Earth Syst. Sci., 16, 2393–2404, https://doi.org/10.5194/hess-16-2393-2012, https://doi.org/10.5194/hess-16-2393-2012, 2012
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Short summary
The rise of new technologies such as drones (unmanned aerial systems – UASs) has allowed widespread use of image velocimetry techniques in place of more traditional, usually slower, methods during hydrometric campaigns. In order to minimize the velocity estimation errors, one must stabilise the acquired videos. In this research, we compare the performance of different UAS video stabilisation tools and provide guidelines for their use in videos with different flight and ground conditions.
The rise of new technologies such as drones (unmanned aerial systems – UASs) has allowed...
